
'''simple docstring'''





import io
import json

import fsspec
import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases







def snake_case_     (					lowercase__   ,       lowercase__		):
  assert isinstance(lowercase__   ,       lowercase__		)
  assert dataset.num_rows == 4
  assert dataset.num_columns == 3
  assert dataset.column_names == ["col_1", "col_2", "col_3"]
  for feature, expected_dtype in expected_features.items():
    assert dataset.features[feature].dtype == expected_dtype







@pytest.mark.parametrize("keep_in_memory"   ,       [False, True]		)
def snake_case_     (					lowercase__   ,       lowercase__   ,       lowercase__		):
  UpperCAmelCase__      :					Dict				       =							tmp_path / "cache"
  UpperCAmelCase__      :					int				       =							{"col_1": "string", "col_2": "int64", "col_3": "float64"}
  with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
    UpperCAmelCase__      :					Optional[Any]				       =							JsonDatasetReader(lowercase__   ,       cache_dir=lowercase__   ,       keep_in_memory=lowercase__		).read()
  _check_json_dataset(lowercase__   ,       lowercase__		)







@pytest.mark.parametrize(
    "features"   ,       [
        None,
        {"col_1": "string", "col_2": "int64", "col_3": "float64"},
        {"col_1": "string", "col_2": "string", "col_3": "string"},
        {"col_1": "int32", "col_2": "int32", "col_3": "int32"},
        {"col_1": "float32", "col_2": "float32", "col_3": "float32"},
    ]   ,       )
def snake_case_     (					lowercase__   ,       lowercase__   ,       lowercase__		):
  UpperCAmelCase__      :					Dict				       =							tmp_path / "cache"
  UpperCAmelCase__      :					str				       =							{"col_1": "string", "col_2": "int64", "col_3": "float64"}
  UpperCAmelCase__      :					int				       =							features.copy() if features else default_expected_features
  UpperCAmelCase__      :					Any				       =							(
      Features({feature: Value(lowercase__		) for feature, dtype in features.items()}		) if features is not None else None
  )
  UpperCAmelCase__      :					Union[str, Any]				       =							JsonDatasetReader(lowercase__   ,       features=lowercase__   ,       cache_dir=lowercase__		).read()
  _check_json_dataset(lowercase__   ,       lowercase__		)







@pytest.mark.parametrize(
    "features"   ,       [
        None,
        {"col_3": "float64", "col_1": "string", "col_2": "int64"},
    ]   ,       )
def snake_case_     (					lowercase__   ,       lowercase__   ,       lowercase__		):
  UpperCAmelCase__      :					Optional[int]				       =							tmp_path / "cache"
  UpperCAmelCase__      :					int				       =							{"col_3": "float64", "col_1": "string", "col_2": "int64"}
  UpperCAmelCase__      :					List[str]				       =							features.copy() if features else default_expected_features
  UpperCAmelCase__      :					Optional[Any]				       =							(
      Features({feature: Value(lowercase__		) for feature, dtype in features.items()}		) if features is not None else None
  )
  UpperCAmelCase__      :					Optional[int]				       =							JsonDatasetReader(lowercase__   ,       features=lowercase__   ,       cache_dir=lowercase__		).read()
  assert isinstance(lowercase__   ,       lowercase__		)
  assert dataset.num_rows == 2
  assert dataset.num_columns == 3
  assert dataset.column_names == ["col_3", "col_1", "col_2"]
  for feature, expected_dtype in expected_features.items():
    assert dataset.features[feature].dtype == expected_dtype







def snake_case_     (					lowercase__   ,       lowercase__		):
  # jsonl_312_path features are {"col_3": "float64", "col_1": "string", "col_2": "int64"}
  UpperCAmelCase__      :					Optional[int]				       =							{"col_2": "int64", "col_3": "float64", "col_1": "string"}
  UpperCAmelCase__      :					List[Any]				       =							features.copy()
  UpperCAmelCase__      :					Any				       =							(
      Features({feature: Value(lowercase__		) for feature, dtype in features.items()}		) if features is not None else None
  )
  UpperCAmelCase__      :					List[str]				       =							tmp_path / "cache"
  UpperCAmelCase__      :					Tuple				       =							JsonDatasetReader(lowercase__   ,       features=lowercase__   ,       cache_dir=lowercase__		).read()
  assert isinstance(lowercase__   ,       lowercase__		)
  assert dataset.num_rows == 2
  assert dataset.num_columns == 3
  assert dataset.column_names == ["col_2", "col_3", "col_1"]
  for feature, expected_dtype in expected_features.items():
    assert dataset.features[feature].dtype == expected_dtype







@pytest.mark.parametrize("split"   ,       [None, NamedSplit("train"		), "train", "test"]		)
def snake_case_     (					lowercase__   ,       lowercase__   ,       lowercase__		):
  UpperCAmelCase__      :					Dict				       =							tmp_path / "cache"
  UpperCAmelCase__      :					List[Any]				       =							{"col_1": "string", "col_2": "int64", "col_3": "float64"}
  UpperCAmelCase__      :					Optional[int]				       =							JsonDatasetReader(lowercase__   ,       cache_dir=lowercase__   ,       split=lowercase__		).read()
  _check_json_dataset(lowercase__   ,       lowercase__		)
  assert dataset.split == split if split else "train"







@pytest.mark.parametrize("path_type"   ,       [str, list]		)
def snake_case_     (					lowercase__   ,       lowercase__   ,       lowercase__		):
  if issubclass(lowercase__   ,       lowercase__		):
    UpperCAmelCase__      :					Tuple				       =							jsonl_path
  elif issubclass(lowercase__   ,       lowercase__		):
    UpperCAmelCase__      :					str				       =							[jsonl_path]
  UpperCAmelCase__      :					int				       =							tmp_path / "cache"
  UpperCAmelCase__      :					Any				       =							{"col_1": "string", "col_2": "int64", "col_3": "float64"}
  UpperCAmelCase__      :					int				       =							JsonDatasetReader(lowercase__   ,       cache_dir=lowercase__		).read()
  _check_json_dataset(lowercase__   ,       lowercase__		)







def snake_case_     (					lowercase__   ,       lowercase__   ,       lowercase__=("train",)		):
  assert isinstance(lowercase__   ,       lowercase__		)
  for split in splits:
    UpperCAmelCase__      :					Dict				       =							dataset_dict[split]
    assert dataset.num_rows == 4
    assert dataset.num_columns == 3
    assert dataset.column_names == ["col_1", "col_2", "col_3"]
    for feature, expected_dtype in expected_features.items():
      assert dataset.features[feature].dtype == expected_dtype







@pytest.mark.parametrize("keep_in_memory"   ,       [False, True]		)
def snake_case_     (					lowercase__   ,       lowercase__   ,       lowercase__		):
  UpperCAmelCase__      :					Union[str, Any]				       =							tmp_path / "cache"
  UpperCAmelCase__      :					Union[str, Any]				       =							{"col_1": "string", "col_2": "int64", "col_3": "float64"}
  with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
    UpperCAmelCase__      :					List[Any]				       =							JsonDatasetReader({"train": jsonl_path}   ,       cache_dir=lowercase__   ,       keep_in_memory=lowercase__		).read()
  _check_json_datasetdict(lowercase__   ,       lowercase__		)







@pytest.mark.parametrize(
    "features"   ,       [
        None,
        {"col_1": "string", "col_2": "int64", "col_3": "float64"},
        {"col_1": "string", "col_2": "string", "col_3": "string"},
        {"col_1": "int32", "col_2": "int32", "col_3": "int32"},
        {"col_1": "float32", "col_2": "float32", "col_3": "float32"},
    ]   ,       )
def snake_case_     (					lowercase__   ,       lowercase__   ,       lowercase__		):
  UpperCAmelCase__      :					Optional[int]				       =							tmp_path / "cache"
  UpperCAmelCase__      :					Tuple				       =							{"col_1": "string", "col_2": "int64", "col_3": "float64"}
  UpperCAmelCase__      :					Any				       =							features.copy() if features else default_expected_features
  UpperCAmelCase__      :					int				       =							(
      Features({feature: Value(lowercase__		) for feature, dtype in features.items()}		) if features is not None else None
  )
  UpperCAmelCase__      :					Union[str, Any]				       =							JsonDatasetReader({"train": jsonl_path}   ,       features=lowercase__   ,       cache_dir=lowercase__		).read()
  _check_json_datasetdict(lowercase__   ,       lowercase__		)







@pytest.mark.parametrize("split"   ,       [None, NamedSplit("train"		), "train", "test"]		)
def snake_case_     (					lowercase__   ,       lowercase__   ,       lowercase__		):
  if split:
    UpperCAmelCase__      :					Any				       =							{split: jsonl_path}
  else:
    UpperCAmelCase__      :					Optional[int]				       =							"train"
    UpperCAmelCase__      :					List[Any]				       =							{"train": jsonl_path, "test": jsonl_path}
  UpperCAmelCase__      :					Union[str, Any]				       =							tmp_path / "cache"
  UpperCAmelCase__      :					str				       =							{"col_1": "string", "col_2": "int64", "col_3": "float64"}
  UpperCAmelCase__      :					Tuple				       =							JsonDatasetReader(lowercase__   ,       cache_dir=lowercase__		).read()
  _check_json_datasetdict(lowercase__   ,       lowercase__   ,       splits=list(path.keys()		)		)
  assert all(dataset[split].split == split for split in path.keys()		)







def snake_case_     (					lowercase__		):
  return json.load(lowercase__		)







def snake_case_     (					lowercase__		):
  return [json.loads(lowercase__		) for line in buffer]






class 							UpperCAmelCase_							:

 '''simple docstring'''







 @pytest.mark.parametrize("lines, load_json_function"			,				[(True, load_json_lines), (False, load_json)] )
 def 							UpperCamelCase  (					self		:  List[Any]			,				snake_case__		:  Any			,				snake_case__		:  Tuple			,				snake_case__		:  int ):



   '''simple docstring'''




   with io.BytesIO() as buffer:
     JsonDatasetWriter(snake_case__			,				snake_case__			,				lines=snake_case__ ).write()
     buffer.seek(0 )
     UpperCAmelCase__      :					Dict				       =							load_json_function(snake_case__ )
   assert isinstance(snake_case__			,				snake_case__ )
   assert isinstance(exported_content[0]			,				snake_case__ )
   assert len(snake_case__ ) == 10







 @pytest.mark.parametrize(
     "orient, container, keys, len_at"			,				[
         ("records", list, {"tokens", "labels", "answers", "id"}, None),
         ("split", dict, {"columns", "data"}, "data"),
         ("index", dict, set("0123456789" ), None),
         ("columns", dict, {"tokens", "labels", "answers", "id"}, "tokens"),
         ("values", list, None, None),
         ("table", dict, {"schema", "data"}, "data"),
     ]			,				)
 def 							UpperCamelCase  (					self		:  str			,				snake_case__		:  Union[str, Any]			,				snake_case__		:  str			,				snake_case__		:  Dict			,				snake_case__		:  int			,				snake_case__		:  Optional[Any] ):



   '''simple docstring'''




   with io.BytesIO() as buffer:
     JsonDatasetWriter(snake_case__			,				snake_case__			,				lines=snake_case__			,				orient=snake_case__ ).write()
     buffer.seek(0 )
     UpperCAmelCase__      :					Union[str, Any]				       =							load_json(snake_case__ )
   assert isinstance(snake_case__			,				snake_case__ )
   if keys:
     if container is dict:
       assert exported_content.keys() == keys
     else:
       assert exported_content[0].keys() == keys
   else:
     assert not hasattr(snake_case__			,				"keys" ) and not hasattr(exported_content[0]			,				"keys" )
   if len_at:
     assert len(exported_content[len_at] ) == 10
   else:
     assert len(snake_case__ ) == 10







 @pytest.mark.parametrize("lines, load_json_function"			,				[(True, load_json_lines), (False, load_json)] )
 def 							UpperCamelCase  (					self		:  str			,				snake_case__		:  str			,				snake_case__		:  Dict			,				snake_case__		:  int ):



   '''simple docstring'''




   with io.BytesIO() as buffer:
     JsonDatasetWriter(snake_case__			,				snake_case__			,				lines=snake_case__			,				num_proc=2 ).write()
     buffer.seek(0 )
     UpperCAmelCase__      :					Tuple				       =							load_json_function(snake_case__ )
   assert isinstance(snake_case__			,				snake_case__ )
   assert isinstance(exported_content[0]			,				snake_case__ )
   assert len(snake_case__ ) == 10







 @pytest.mark.parametrize(
     "orient, container, keys, len_at"			,				[
         ("records", list, {"tokens", "labels", "answers", "id"}, None),
         ("split", dict, {"columns", "data"}, "data"),
         ("index", dict, set("0123456789" ), None),
         ("columns", dict, {"tokens", "labels", "answers", "id"}, "tokens"),
         ("values", list, None, None),
         ("table", dict, {"schema", "data"}, "data"),
     ]			,				)
 def 							UpperCamelCase  (					self		:  Optional[int]			,				snake_case__		:  Optional[int]			,				snake_case__		:  Optional[int]			,				snake_case__		:  List[Any]			,				snake_case__		:  List[str]			,				snake_case__		:  Union[str, Any] ):



   '''simple docstring'''




   with io.BytesIO() as buffer:
     JsonDatasetWriter(snake_case__			,				snake_case__			,				lines=snake_case__			,				orient=snake_case__			,				num_proc=2 ).write()
     buffer.seek(0 )
     UpperCAmelCase__      :					Union[str, Any]				       =							load_json(snake_case__ )
   assert isinstance(snake_case__			,				snake_case__ )
   if keys:
     if container is dict:
       assert exported_content.keys() == keys
     else:
       assert exported_content[0].keys() == keys
   else:
     assert not hasattr(snake_case__			,				"keys" ) and not hasattr(exported_content[0]			,				"keys" )
   if len_at:
     assert len(exported_content[len_at] ) == 10
   else:
     assert len(snake_case__ ) == 10







 def 							UpperCamelCase  (					self		:  str			,				snake_case__		:  int ):



   '''simple docstring'''




   with pytest.raises(snake_case__ ):
     with io.BytesIO() as buffer:
       JsonDatasetWriter(snake_case__			,				snake_case__			,				num_proc=0 )







 @pytest.mark.parametrize("compression, extension"			,				[("gzip", "gz"), ("bz2", "bz2"), ("xz", "xz")] )
 def 							UpperCamelCase  (					self		:  List[Any]			,				snake_case__		:  Any			,				snake_case__		:  int			,				snake_case__		:  Dict			,				snake_case__		:  Dict			,				snake_case__		:  List[Any] ):



   '''simple docstring'''




   UpperCAmelCase__      :					Any				       =							tmp_path_factory.mktemp("data" ) / F"""test.json.{extension}"""
   UpperCAmelCase__      :					Tuple				       =							str(shared_datadir / F"""test_file.json.{extension}""" )
   JsonDatasetWriter(snake_case__			,				snake_case__			,				compression=snake_case__ ).write()

   with fsspec.open(snake_case__			,				"rb"			,				compression="infer" ) as f:
     UpperCAmelCase__      :					List[str]				       =							f.read()
   with fsspec.open(snake_case__			,				"rb"			,				compression="infer" ) as f:
     UpperCAmelCase__      :					Any				       =							f.read()
   assert exported_content == original_content




from __future__ import annotations

import math

import numpy as np
from numpy.linalg import norm


def 	lowerCamelCase					(	UpperCamelCase     :				np.ndarray			,       UpperCamelCase     :				np.ndarray							)   ->    float:
		return math.sqrt(sum(pow(a - b			,       2							) for a, b in zip(UpperCamelCase			,       UpperCamelCase							)							)							)


def 	lowerCamelCase					(	UpperCamelCase     :				np.ndarray			,       UpperCamelCase     :				np.ndarray							)   ->    list[list[list[float] | float]]:

		if dataset.ndim != value_array.ndim:
				_lowerCamelCase				   =  (
				    'Wrong input data\'s dimensions... '
				    F"""dataset : {dataset.ndim}, value_array : {value_array.ndim}"""
				)
				raise ValueError(UpperCamelCase							)

		try:
				if dataset.shape[1] != value_array.shape[1]:
						_lowerCamelCase				   =  (
						    'Wrong input data\'s shape... '
						    F"""dataset : {dataset.shape[1]}, value_array : {value_array.shape[1]}"""
						)
						raise ValueError(UpperCamelCase							)
		except IndexError:
				if dataset.ndim != value_array.ndim:
						raise TypeError('Wrong shape'							)

		if dataset.dtype != value_array.dtype:
				_lowerCamelCase				   =  (
				    'Input data have different datatype... '
				    F"""dataset : {dataset.dtype}, value_array : {value_array.dtype}"""
				)
				raise TypeError(UpperCamelCase							)

		_lowerCamelCase				   =  []

		for value in value_array:
				_lowerCamelCase				   =  euclidean(UpperCamelCase			,       dataset[0]							)
				_lowerCamelCase				   =  dataset[0].tolist()

				for dataset_value in dataset[1:]:
						_lowerCamelCase				   =  euclidean(UpperCamelCase			,       UpperCamelCase							)

						if dist > temp_dist:
								_lowerCamelCase				   =  temp_dist
								_lowerCamelCase				   =  dataset_value.tolist()

				answer.append([vector, dist]							)

		return answer


def 	lowerCamelCase					(	UpperCamelCase     :				np.ndarray			,       UpperCamelCase     :				np.ndarray							)   ->    float:
		return np.dot(UpperCamelCase			,       UpperCamelCase							) / (norm(UpperCamelCase							) * norm(UpperCamelCase							))


if __name__ == "__main__":
				import doctest

				doctest.testmod()